Server consolidation using virtualization technology virtualizes several hundred to several thousand servers (consolidation subject servers) in an enterprise to consolidate them into a smaller number of high-performance servers (consolidation destination servers). To have a plurality of servers operate on a single physical server, it is necessary to estimate the resource capacity of each consolidation destination server, the number of consolidation destination servers, and a combination of a consolidation subject server and a consolidation destination server so that the resources (a CPU, a disk, a network, etc.) required by the server to be consolidated can be accommodated into the resource capacity of the consolidation destination server.
It is therefore necessary to collect the operational resource utilization amounts (a CPU utilization rate, a disk utilization amount, etc.) of consolidation subject servers, and, based on the collected information and the resource capacity of consolidation destination servers, to calculate a combination of a consolidation subject server and a consolidation destination server that distributes the resource utilization amounts equally without exceeding the resource capacity of the consolidation destination server.
In Non-Patent Literature 1, the problem of calculating a combination of a consolidation subject server and a consolidation destination server in server consolidation using virtualization technology is discussed as the bin packing problem (a problem of packing items of different volumes into a finite number of bins in a way that minimizes the number of bins used). This problem is solved by using an improved First-Fit Decreasing (FFD) algorithm, which is one of heuristic solutions. In the improved FFD, if the capacity of bins is exceeded, instead of immediately adding a new bin, the item that failed to be packed is treated as a large item of an unnoticed dimension and the order of items is altered so that this item is packed first. A threshold is set to the number of times the order of items is altered. If the threshold is exceeded, a new bin is added. By altering the order of items in this way, an excessive increase of the number of bins is prevented to achieve optimization.
According to this literature, by considering an unnoticed dimension by reordering, an optimum solution is obtained with low computational cost. However, only one dimension is considered, and it is not possible to consider a plurality of dimensions such as CPUs and disks, or to consider priorities. A method has been devised for measuring the system load from a plurality of virtual machines in operation and computing a combination of virtual machines that maximizes the performance in a virtualized environment.
On the other hand, Patent Literature 1 teaches a method of optimally allocating hosting service resources. This invention teaches a method of modeling the utilization patterns of clients and allocating a combination of clients to a server in a way that disperses the peaks of individual utilization patterns. For allocation, the use of FFD is also discussed.    Patent Literature 1: JP 2002-318791 A    Non-Patent Literature 1: Yasuhiro Ajiro, Atsuhiro Tanaka, “A Combinatorial Optimization Algorithm for Server Consolidation”, The 21st Annual Conference of the Japanese Society for Artificial Intelligence, 2007